Application of Texture Analysis and Kohonen Map for Region Segmentation of Pavement Images for Crack Detection
The first phase of a research study on detecting cracks in pavements is described. For reliable crack detection, various regions in a road image have to be segmented accurately. A procedure based on the texture and color properties of different regions of images is used in conjunction with the Kohonen map, also known as the self-organizing map. Accuracy of 89.7% was obtained with classification based on the Kohonen map of images taken with a regular digital camera and simple lighting setup. Furthermore, a complementary algorithm is described to remove spurious classifications caused by inaccuracies in the trained Kohonen map. With the help of this algorithm, an overall segmentation accuracy of 97.7% is reported. This research is expected to affect other problems in transportation engineering, such as road boundary detection and road marking inspection. The detection of cracks from the segmented regions will be addressed in the future.
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- Summary URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780309263030
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Authors:
- Mathavan, S
- Rahman, M M
- Kamal, K
- Publication Date: 2012
Language
- English
Media Info
- Media Type: Print
- Features: Figures; References; Tables;
- Pagination: pp 150–157
- Monograph Title: Pavement Management 2012, Volume 1
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Serial:
- Transportation Research Record: Journal of the Transportation Research Board
- Issue Number: 2304
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Algorithms; Detection and identification; Digital cameras; Image processing; Pavement cracking; Texture
- Uncontrolled Terms: Kohonen feature map
- Subject Areas: Highways; Maintenance and Preservation; Pavements; I23: Properties of Road Surfaces; I60: Maintenance;
Filing Info
- Accession Number: 01373800
- Record Type: Publication
- ISBN: 9780309263030
- Report/Paper Numbers: 12-2066
- Files: TRIS, TRB, ATRI
- Created Date: Jun 25 2012 4:18PM